Symposium in Modelling of Terrestrial
Systems and Evolution, Ouro Preto, 2011
Modelling Human-Environment
Interactions with TerraME
Gilberto Câmara (INPE)
Tiago Carneiro (UFOP)
Pedro Andrade Neto (INPE)
Licence: Creative Commons By Attribution Non Commercial Share Alike
http://creativecommons.org/licenses/by-nc-sa/2.5/
The fundamental question of our time
By 2050...
8,5 billion people: 6 billion
tons of GHG and 60 million
tons of urban pollutants.
Resource-hungry: We will
withdraw 30% of available
fresh water.
How is the Earth’s environment
changing, and what are the
consequences for human
civilization?
fonte: IGBP
Planetary Boundaries
http://www.stockholmresilience.org/
Human actions and global change
photo: C. Nobre
Global Change
Where are changes taking place?
How much change is happening?
Who is being impacted by the change?
What is causing change?
photo: A. Reenberg
Is Computing a natural science?
“Computer science is not actually a science. It does not study
natural objects. It’s about getting to do something, rather than
dealing with abstractions.” (Richard Feynman)
Is Computing a natural science?
“Computing is the study of natural and artificial information
processes.” (Peter Denning)
What’s in an image?
What’s in an image?
Web map (Barabasi)
(could be brain connections or between scientists)
Information flows in nature
Ant colonies live in a chemical world
Conections and flows are universal
Yeast proteins
(Barabasi and Boneabau,
SciAm, 2003)
Scientists in Silicon Valley
(Fleming and Marx, Calif Mngt
Rew, 2006)
Information flows generate cooperation
National Cancer Institute, EUA
http://visualsonline.cancer.gov
White cells attact a cancer cell (cooperative activity)
Tragedy of the Commons?
Everybody’s property is nobody’s property (Hardin)
Is the tragedy of the commons inevitable?
Experiments show that cooperation emerges if virtuous
interactions exist
source: Novak, May and Sigmund (Scientific American, 1995)
Common pool resources (Elinor Ostrom)
The ultimate common pool resource
Governing the commons:
institutional arrangments
[Ostrom, Science, 2005]
Elinor Ostrom on governing the commons
“Neither the state nor the market is uniformly successful in
enabling individuals to sustain long-term, productive use of
natural resource systems.”
Building information models
Connect expertise from different fields
Make the different conceptions explicit
Territory
(Geography)
Money
(Economy)
Modelling
(Computing)
Culture
(Antropology)
1973
1987
2000
Slides from LANDSAT
images: USGS
Modelling Human-Environment Interactions
How do we decide on the use of natural resources?
What are the conditions favoring success in resource mgnt?
Can we anticipate changes resulting from human decisions?
What techniques and tools are needed to model humanenvironment decision making?
We need spatially explicit models to
understand human-environment interactions
Nature: Physical equations
Describe processes
Society: Decisions on how to
Use Earth´s resources
Dynamic Spatial Models
f (It)
f (It+1)
F
f (It+2)
f ( It+n )
F
..
“A dynamical spatial model is a computational representation
of a real-world process where a location on the earth’s surface
changes in response to variations on external and internal
dynamics on the landscape” (Peter Burrough)
Question #1 for human-environment models
What social theories and concepts are required for humanenvironment models? Can they be translated into
information systems?
Fields
Cells (objects)
Concepts for spatial dynamical models
Events and processes
Resilience
Concepts for spatial dynamical models
vulnerability
degradation
Concepts for spatial dynamical models
biodiversity
sustainability
and much more…
Human-environmental models need to describe complex
concepts (and store their attributes in a database)
We need social theories to understand humanenvironment interactions




Social simulation
Schelling, “Micromotives and macrobehavior” (1978).
Batty, “Cities and complexity” (2005).
Game theory
von Neumann and Morgenstern, “Theory of games and economic
behavior” (1944)
Nash, "Equilibrium points in n-person games“ (1950).
Evolutionary dynamics
Maynard Smith, ”Evolution and the theory of games” (1982)
Axelrod, “Evolution of cooperation” (1988).
Novak, “Evolutionary dynamics: exploring the equations of life”
(2005).
Institutional analysis
Ostrom, “Governing the commons” (1990).
Game Theory
GT is an analytical tool for social sciences that is used to model
strategic interactions or conflict situations.
Strategic interaction: When actions of a player influence payoffs
to other players
Where can we use Game Theory?
Any situation that requires us to anticipate our rival’s response to
our action is a potential context for GT.
Economics, Political science, Biology
Question #2 for human-environment models
What models are needed to describe human actions?
Clouds: statistical distributions
Clocks, clouds or ants?
Clocks: deterministic equations
Ants: emerging behaviour
Statistics: Humans as clouds
y=a0 + a1x1 + a2x2 + ... +aixi +E
Establishes statistical relationship with variables that are related
to the phenomena under study
Basic hypothesis: stationary processes
Fonte: Verburg et al, Env. Man., Vol. 30, No. 3, pp. 391–405
Amazônia in 2007 x All Variables
Variables
Transportation (11)
Distance Markets(7)
Demography (3)
Tecnology (2)
Environmental (20)
Public Policy(8)
Market (8)
Agrarian Structure(6)
Agents as basis for complex systems
An agent is any actor within an environment, any entity
that can affect itself, the environment and other agents.
Agent: flexible, interacting and autonomous
Modelling collective spatial actions
Agent
Agent
Space
Space
Benenson and Torrens, “Geographic Automata Systems”, IJGIS, 2005
(but many questions remain...)
Question #3 for human-environment models
What types of spatial relations exist in
nature-society models?
Natural space is (usually) isotropic
Societal space is mostly anisotropic
1975
Rondonia
1986
Societal spaces are connected
Which spatial objects are
closer?
Which cells are closer?
[Aguiar et al., 2003]
Requirement #3 for human-environment models:
express connections explicitly
Euclidean space
Closed network
Open network
D1
D2
[Aguiar et al., 2003]
Question #4 for human-environment models
How do we combine
independent multi-scale
models with feedback?
Models: From Global to Local
Athmosphere, ocean, chemistry
climate model (200 x 200 km)
Atmosphere only global climate
model (50 x 50 km)
Regional climate model (10 x 10 km)
Hydrology, Vegetation
Soil Topography (1 x 1 km)
Regional land use change
Socio-economic adaptation (e.g.,
100 x 100 m)
Question #5 for human-environment models
photos: Isabel Escada
How can we express behavioural changes in
human societies?
Small Farmers
When a small
farmer becomes a
medium-sized one,
his behaviour
changes
Medium-Sized Farmers
Societal systems undergo phase transitions
latency
> 6 years
Deforesting
Newly implanted
Small Farmers
Deforestation >
80%
Year of
creation
Slowing down
Iddle
Deforestation =
100%
photos: Isabel Escada
Deforesting
Deforestation >
60%
Year of
creation
Slowing down
Iddle
Deforestation =
100%
Medium-Sized
Farmers
TerraLib: spatio-temporal database as a basis for
innovation
G. Câmara et al.“TerraLib: An open-source GIS library for large-scale environmental
and socio-economic applications”. In: B. Hall, M. Leahy (eds.), “Open Source
Approaches to Spatial Data Handling”. Berlin, Springer, 2008.
Visualization (TerraView)
Modelling (TerraME)
Spatio-temporal
Database (TerraLib)
Statistics (aRT)
Data Mining(GeoDMA)
TerraME: Computational environment for
developing human-environment models
Cell Spaces
Support for cellular
automata and agents
http://www.terrame.org
[Carneiro, 2006]
Spatial structure in TerraME: Cell Spaces
integrated with databases
TerraME´s approach: Modular components
[Carneiro, 2006]
1. Get first pair
2. Execute the ACTION
3. Timer =EVENT
1.
1:32:00
Mens. 1
2.
1:32:10
Mens. 3
3.
1:38:07
Mens. 2
4.
1:42:00
Mens.4
...
return value
true
4. timeToHappen += period
Describe spatial structure
latency
> 6 years
Describe temporal structure
Deforesting
Newly implanted
Year of
creation
Iddle
Slowing down
Deforestation =
100%
Describe rules of behaviour
Describe spatial relations
TerraME: multi-scale modelling using explicit
relationships
[Moreira et al., 2008]
[Carneiro et al., 2008]
Scale 1
father
up-scaling
children
Scale 2
Generalized proximity matrices
express explicit spatial relationships
between individual objects in
different scales
 w11
w
W   21
 w31

 w41
w12 w13 w14 
w22 w23 w24 
w32 w33 w34 

w42 w43 w44 
GPM: Relations between cells and agents
a
From
Cell
Agent
Agent
To
Cell
a
[Andrade-Neto et
al., 2008]
b
c
b
c
TerraME uses hybrid automata to represent phase
transitions
A hybrid automaton is a formal model for a mixed
discrete continuous system (Henzinger, 1996)
Hybrid Automata = state machine + dynamical systems
State A
Flow
Condition
State B
Jump
condition
Flow
Condition
Hybrid automata: simple land tenure model
Farmer gets parcel
SUBSISTENCE deforest>=60%
CATTLE
Deforest 20%/year
Extensive cattle raising
LAND REFORM
redistribution
Land exhaustion
Land revision ABANDONMENT
RECLAIM
Land registration
Public repossession
Regrowth
STATE
Flow Condition
Jump Condition
Transition
SUBSISTENCE
Deforest 10% of land/year
Deforest > 60%
CATTLE
CATTLE
Extensive cattle raising
Land exhaustion
ABANDONMENT
ABANDONMENT
Forest regrowth
Land revision
RECLAIM
RECLAIM
Public repossession
Land registration
LAND REFORM
LAND REFORM
Land distribution
Farmer gets
parcels
SUBSISTENCE
Where is Lua?

Inside Brazil
Petrobras, the Brazilian Oil Company
 Embratel
(the main telecommunication
company in Brazil)
TerraME
Programming
Language: Extension
of LUA
 many other companies

LUA
the language
of choice for computer games
 is
Outside
Brazil


Lua is used in hundreds of projects, both commercial and academic
CGILua still in restricted use

until recently all documentation was in Portuguese
Lua and the Web
source: the LUA team
[Ierusalimschy et al, 1996]
TerraME programming environment
TerraME INTERPRETER
• model syntax semantic checking
• model execution
TerraView
• data acquisition
• data visualization
• data management
• data analysis
LUA interpreter
TerraME framework
data
model
model
TerraME/LUA interface
data
Eclipse & LUA plugin
• model description
• model highlight syntax
MODEL DATA
Model
source code
TerraLib
database
[Carneiro, 2006]
Can we avoid that this….
Source: Carlos Nobre (INPE)
Fire...
….becomes this?
Source: Carlos Nobre (INPE)
~230 scenes
Landsat/year
Deforestation in Amazonia
Amazonia: multiscale analysis of land change and
beef and milk market chains with TerraME
São Felix do Xingu
INPE/PRODES 2003/2004:
Deforestation
Forest
Non-forest
Clouds/no data
Landscape model: different rules for two main
types of actors
Beef and milk
market chain model
Land use
Change model
Small
farmers
Medium
and large
farmers
Landscape
metrics
model
Pasture
degradation
model
Several workshops to define model rules and variables
Small farmers in Amazonia
Settlement/
invaded land
Sustainability path
(alternative uses, technology)
Diversify use
money surplus
Subsistence
agriculture
Create pasture/
Deforest
Manage cattle
bad land
management
Move towards
the frontier
Sustainability
path (technology)
Abandon/Sell
the property
Buy new
land
Speculator/
large/small
Large farmers in Amazonia
Diversify use
money surplus/bank loan
Buy land
from small
farmers
Create pasture/
plantation/
deforest
Manage cattle/
plantation
Buy new
land
Buy calves
from small
Speculator/
large/small
Regional scale
Frontier
INDIVIDUAL AGENTS
Large and small farmers
Local scale
SCENARIOS
LANDSCAPE DYNAMICS MODEL
- Front
- Medium
- Rear
Local farmers
Region
CATTLE CHAIN MODEL
Flows: goods, information, etc..
Connections: Agents
Landscape model: different rules of behavior at different
partitions which also change in time
SÃO FÉLIX DO XINGU - 2006
FRONT
FRENTE
MIDDLE
MEIO
BACK
RETAGUARDA
Forest
River
Deforest
Not Forest
Modeling results
97 to 2006
Observed
97 to 2006
Some caution necessary...
“Complexity is more and more acknowledged to
be a key characteristic of the world we
live in and of the systems that cohabit our
world. It is not new for science to attempt to
understand complex systems: astronomers have
been at it for millennia, and biologists,
economists, psychologists, and others joined
them some generations ago. (…)
If, as appears to be the case, complexity (like
systems science) is too general a subject
to have much content, then particular classes of
complex systems possessing strong
properties that provide a fulcrum for theorizing
and generalizing can serve as the foci
of attention.”
(from “The Sciences of the Artificial”, 1996)
Herbert Simon (1958)
Modelling human-environment interactions
1.
2.
3.
4.
Situated individuals
Interaction rules: semantics of communication
Decision rules
Properties of space
Conclusion
Computing can make a significant contribution to global change
research, supporting spatially explicit models of humanenvironment interactions with reasoned scientific basis